The goal of the Affordable Care Act (ACA) was to achieve nearly universal health insurance coverage through a combination of mandates, subsidies, marketplaces, and Medicaid expansions, most of which took effect in 2014. We use data from the Behavioral Risk Factor Surveillance System to examine the impacts of the ACA on health care access, risky health behaviors, and self-assessed health after two years. We estimate difference-in-difference-in-differences models that exploit variation in treatment intensity from state participation in the Medicaid expansion and pre-ACA uninsured rates. Results suggest that the ACA led to sizeable improvements in access to health care in both Medicaid expansion and non-expansion states, with the gains being larger in expansion states along some dimensions. N...

The Affordable Care Act (ACA) aimed to achieve nearly universal health insurance coverage in the United States through a combination of insurance market reforms, mandates, subsidies, health insurance exchanges, and Medicaid expansions, most of which took effect in 2014. This paper estimates the causal effects of the ACA on health insurance coverage using data from the American Community Survey. We utilize difference-in-difference-in-differences models that exploit cross-sectional variation in the intensity of treatment arising from state participation in the Medicaid expansion and local area pre-ACA uninsured rates. This strategy allows us to identify the effects of the ACA in both Medicaid expansion and non-expansion states. Our preferred specification suggests that, at the average pre-tr...

In 2006, Massachusetts passed health care reform legislation designed to achieve nearly universal coverage through a combination of insurance market reforms, mandates, and subsidies that later served as the model for national reform. Using data from the Behavioral Risk Factor Surveillance System, we provide evidence that health care reform in Massachusetts led to better overall self-assessed health. Various robustness checks and placebo tests support a causal interpretation of the results. We also document improvements in several determinants of overall health: physical health, mental health, functional limitations, joint disorders, and body mass index. Next, we show that the effects on overall health were strongest among those with low incomes, non-whites, near-elderly adults, and women. ...